Here you save the model architecture (encoder_model), but instead you should save pretrained_model which is the final pretrained model that you should use for finetuning afterwards
Standalone code to reproduce the issue or tutorial link
# Save this base model for further finetuning.
encoder_model.save("encoder_model.keras")
This line under https://github.com/keras-team/keras-io/tree/master/guides/keras_nlp/transformer_pretraining.py
Here you save the model architecture (encoder_model), but instead you should save pretrained_model which is the final pretrained model that you should use for finetuning afterwards
Relevant log output
# Save this base model for further finetuning.
encoder_model.save("encoder_model.keras")
This line under https://github.com/keras-team/keras-io/tree/master/guides/keras_nlp/transformer_pretraining.py
Here you save the model architecture (encoder_model), but instead you should save pretrained_model which is the final pretrained model that you should use for finetuning afterwards
Issue Type
Bug
Source
source
Keras Version
Keras 2.14
Custom Code
Yes
OS Platform and Distribution
No response
Python version
No response
GPU model and memory
No response
Current Behavior?
Save this base model for further finetuning.
encoder_model.save("encoder_model.keras")
This line under https://github.com/keras-team/keras-io/tree/master/guides/keras_nlp/transformer_pretraining.py
Here you save the model architecture (encoder_model), but instead you should save pretrained_model which is the final pretrained model that you should use for finetuning afterwards
Standalone code to reproduce the issue or tutorial link
Relevant log output